Automatically audit Confluence spaces for anonymous access and public links, generating per-space reports to support compliance and data-leakage prevention.
This AI agent scans selected Confluence spaces to identify anonymous access permissions and public exposure risks. It checks whether public links are enabled and which pages are shared publicly. It outputs a consolidated per-space report detailing anonymous access status, public link status, and the pages exposed to support compliance reviews.
Consolidated per-space findings with actionable exposure details.
Detects anonymous access permissions at each space.
Checks public link enablement at each space.
Fetches pages with public links and their statuses.
Merges results into a single per-space report.
Annotates findings with space permissions and exposure details.
Exports a report usable for audits and reviews.
Before this AI agent, audits were manual, time-consuming, and prone to missing exposure. After implementing the AI agent, you get centralized, up-to-date visibility with clear remediation guidance.
Three-step system flow that is easy for non-technical users to understand.
Manual trigger to start the audit and set variables like atlassianDomain and spaceKeys.
Get spaces via REST (v2) and run three GraphQL queries in parallel for anonymous access, public link status, and pages with public links.
Merge results into a per-space report and present a consolidated output for review.
One realistic scenario.
A security administrator runs the AI agent against ENG and HR Confluence spaces as part of a quarterly compliance check. The agent completes in about 12–15 minutes and outputs a per-space report listing anonymous access status, public link status, and exposed pages, with remediation suggestions.
One supporting sentence.
Needs clear visibility into exposure across Confluence spaces.
Requires auditable data and concrete evidence of controls.
Enforces access controls and mitigates exposure risk.
Monitors ongoing exposure and triages findings.
Aligns with data leakage prevention requirements.
Produces objective, repeatable audit data.
One supporting sentence with short explanation.
Discover spaces, permissions, and exposure data
Fetch anonymous access, public-link status, and pages with public links
Authenticate calls to REST and GraphQL endpoints
One supporting sentence with short explanation.
One supporting sentence with short explanation.
The agent reads space metadata, anonymous access settings, public link status, and the list of pages with public exposure through Confluence REST and GraphQL endpoints. It does not retrieve page contents or modify permissions. Credentials used for access are stored securely and only used to read data necessary for the audit. Data collected is organized into per-space reports to facilitate review and remediation. No raw data from pages is exported outside the audit report. The workflow is designed to minimize data exposure and adhere to your security policies.
Yes. The AI agent supports a manual trigger and can be configured to run on a schedule or via a deployment pipeline. Scheduling ensures regular visibility into space permissions and public exposure. You can set the cadence to align with your compliance calendar, e.g., weekly or monthly audits. Outputs are consolidated per run to support trend analysis and regulatory reporting.
The audit requires read access to Confluence spaces, space permissions, and GraphQL endpoints. You will need an Atlassian account with an API token and email used to authenticate REST and GraphQL calls. The credential should be scoped to allow space discovery and permission reads. It does not require write access or modification permissions. Always secure credentials and rotate them as part of your standard security hygiene.
A per-space report detailing anonymous access status, public link enablement, and pages with public links. Each entry includes the space name, the exposure status, and a list of affected pages with their status. The report is structured for quick review by security and compliance teams and supports remediation tracking. The agent does not disclose page contents; it focuses on exposure metadata and ownership where available.
Runs are designed to be stateless by default, with data retained only for the duration of the audit. If you enable archival storage, data can be written to secure storage per your policy, with access controls and retention limits. You should define retention windows in your data governance framework. Sensitive data is not published outside the audit output. You can automate deletion or anonymization after review to minimize risk.
The agent audits only the spaces you specify in spaceKeys and will report their exposure status accordingly. Private spaces are not altered and will remain inaccessible if they are not selected. The tool provides visibility into which spaces expose data publicly so you can remediate as needed. If a space becomes public, it will appear in the per-space report so owners can take action.
The current focus is Confluence, using REST v2 and GraphQL endpoints exposed by Confluence. It does not directly manage or audit Jira or other Atlassian products. You can integrate remediation workflows in Jira if needed, but the agent’s out-of-the-box capability centers on Confluence space permissions and public links. For broader coverage, consider extending the integration layer with product-specific APIs in your environment.
Automatically audit Confluence spaces for anonymous access and public links, generating per-space reports to support compliance and data-leakage prevention.
